Estimation of daily reference evapotranspiration by hybrid singular spectrum analysis-based stochastic gradient boosting

Eyyup Ensar Başakın*, Ömer Ekmekcioğlu, Paul C. Stoy, Mehmet Özger

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

In this study, stochastic gradient boosting (SGB), a commonly-adopted soft computing method, was used to estimate reference evapotranspiration (ETo) for the Adiyaman region of southeastern Türkiye. The FAO-56-Penman-Monteith method was used to calculate ETo, which we then estimated using SGB with maximum temperature, minimum temperature, relative humidity, wind speed, and solar radiation obtained from a meteorological station. • The calculated ETo time series values were decomposed into sub-series using Singular Spectrum Analysis (SSA) to enhance prediction accuracy. • Each sub-series was trained with the first 70% of observations and tested with the remaining 30% via SGB. Final prediction values were obtained by collecting all series predictions. • Three lag times were taken into account during the predictions, and both short-term and long-term ETo values were estimated using the proposed framework. The results were tested with respect to root mean square error (RMSE) and Nash-Sutcliffe efficiency (NSE) indicators for ensuring whether the model produced statically acceptable outcomes.

Original languageEnglish
Article number102163
JournalMethodsX
Volume10
DOIs
Publication statusPublished - Jan 2023

Bibliographical note

Publisher Copyright:
© 2023 The Author(s)

Funding

We would like to thank Meteorological General Institution for providing meteorological data. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

FundersFunder number
Meteorological General Institution

    Keywords

    • Estimation
    • Reference evapotranspiration
    • Singular spectrum analysis
    • Stochastic gradient boosting

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